Data and Decision Analytics: Advanced
Enrol
4 days
In-Person, On-Campus
¶¶Òõ¶ÌÊÓƵ City Campus
$4,400.00
Accelerate your career, learn new skills, and expand your knowledge.
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Overview
Analytics refers to a systematic, quantitative, iterative and interactive approach to addressing and evaluating important decision choices confronted by organisations in the private and public sectors.ÌýThisÌýshort course on AdvancedÌýData and Decision Analytics is designed to cover some advanced topics on the principles and practices of data and decision analytics, to introduce data and decision-making tools for analysing complex problem environments, and for making appropriate decisions within that environment, and to strengthen the individual’s decision-making skills.Ìý
Course content
This course addresses some advanced data and decision analytics problems. It introduces analytical tools for integer decision-making, goal achievement and multiple objectives, sensitivity analysis, regression and time-series data insights, and data clustering. Examples of problems that can be solved using an Add-in to Excel (Solver) are covered. Problems involving mix-planning decisions, capital budgeting, manpower planning, managing tasks and resources in projects, prediction, clustering decisions, and waiting line analysis, to name a few, will be presented. AI/CI/Evolutionary Computation-based decision problems solving will be discussed.
Learning outcomes
Skills/competencies/knowledge that would be gained through this course:
- Gaining data and decision-making skills
- ¶¶Òõ¶ÌÊÓƵ certificate of completion/attendance
- Masters credit: ¶¶Òõ¶ÌÊÓƵ allows students who have successfully completed a minimum of 12 days of approved professional education short courses to use those courses as credit in eligible postgraduate programs.
Who should attend
Ìý
The course is valuable for anyone faced with complex and continually changing data and decision problems in public or private sector organisations or communities.
Prerequisites
‘Data and Decision Analytics: Introduction’ is a prerequisite for this course or an equivalent knowledge.Ìý
Facilitator
Prof. Ruhul A Sarker
Professor Ruhul A. SarkerÌýobtained his PhD in Operations Research from Dalhousie University (former TUNS), Halifax, Canada, in 1992. He is currently a professor at the School of Systems & Computing, a former coordinator of the Master of Decision Analytics program, and a former director of the Faculty Postgraduate Research at ¶¶Òõ¶ÌÊÓƵ (2015–2020). He also served as the Deputy Head of School (Research) from 2011–2014. Prof. Sarker’s broad teaching and research interests include decision analytics, computational intelligence, operations research, applied optimisation and simulation. He's the lead author of the bookÌýOptimization Modelling: A Practical Approach, Taylor & Francis /CRC Press, Boca Raton. He was a member of the Australian Society for Operations Research (ASOR) national executive committee and Editor-in-Chief ofÌýthe ASOR BulletinÌýfrom 2000–2011. In recognition of Prof. Sarker’s contributions to ASOR and Operations Research, ASOR awarded him an ASOR Medal (2011) and Special Service Certificate (2009). He also received the ¶¶Òõ¶ÌÊÓƵ Service Award.
Cancellation policy
Courses will be held subject to sufficient registrations. ¶¶Òõ¶ÌÊÓƵ reserves the right to cancel a course up to five working days prior to commencement of the course. If a course is cancelled, you will have the opportunity to transfer your registration or be issued a full refund. If registrant cancels within 10 days of course commencement, a 50% registration fee will apply. ¶¶Òõ¶ÌÊÓƵ is a registered ACT provider under ESOS Act 2000-CRICOS provider Code 00098G.